Web Acceptance and Usage Model: A Comparison between Goal-directed and Experiential Web Users

Au ho Ma ke ing P o esso , Manuel J. Sánchez-F anco, Ph. D. Business P o esso , José L. Roldán, Ph. D. Ti le Web Accep ance and Usage Model: A Compa ison be ween Goal-di ec ed and Expe ien ial Web Use s Add ess: English Spanish Business Adminis a ion Facul y Uni e si y o Se ille A da. Ramón y Cajal, nº 1 41018-Se ille Spain Facul ad de Ciencias Económicas y Emp esa iales Depa amen o de Adminis ación de Emp esas y Ma ke ing Uni e sidad de Se illa A da. Ramón y Cajal, nº 1 41018-Se illa España P o esso Sánchez-F anco's esea ch e o s ocus on In e ne ma ke ing s a egy, consume beha iou in online en i onmen s, and psychological p ocesses and Web ad e ising e ec s. P o esso Roldán's esea ch e o s ocus on execu i e in o ma ion sys ems (EIS), in o ma ion sys em e ec i eness, knowledge managemen , and pa ial leas squa es. Mail- o: [email p o ec ed] jl [email protected] Phone: 0034.954.55.96.68 / 0034.954.55.44.58 Fax: 0034.954.55.69.89 2 Abs ac In his pape we analyse he Web accep ance and usage be ween goal-di ec ed use s and expe ien ial use s, inco po a ing in insic mo i es o imp o e he pa icula and explana o y TAM alue – adi ionally ela ed o ex insic mo i es-. A ield s udy was conduc ed o alida e measu es used o ope a ionalize model a iables and o es he hypo hesised ne wo k o ela ionships. The da a analysis me hod used was Pa ial Leas Squa es (PLS). The empi ical esul s p o ided s ong suppo o he hypo heses, highligh ing he oles o low, ease o use and use ulness in de e mining he ac ual use o he Web among expe ien ial and goal-di ec ed use s. In con as wi h p e ious esea ch ha sugges s ha low would be mo e likely o occu du ing expe ien ial ac i i ies han goal-di ec ed ac i i ies, we ound clea e idence o low o goal-di ec ed ac i i ies. In pa icula he s udy indings indica e ha low migh play a powe ul ole in de e mining he a i ude owa ds usage, in en ion o use and, in u n, ac ual Web use among expe ien ial and goal-di ec ed use s. Keywo ds: TAM, low, use ulness, ease o use, enjoymen , expe ien ial beha iou , goal-di ec ed beha iou 3 INTRODUCTION Few s udies ocus di ec ly (1) on Web accep ance and usage adop ing a use -cen ed pe spec i e, and (2) on he mo i es ha a ec beha iou . In ac , No ak e al. (2000) sugges ha among ma ke ing academics and In e ne p ac i ione s alike, he e is a lack o genuine knowledge abou he ac o s ha b ing abou e ec i e in e ac ions wi h online cus ome s. Mo e ecen ly, Pa asu aman and Zinkhan (2002) poin ou ha he e is a conside able knowledge gap be ween he p ac ice o online ma ke ing and he a ailabili y o sound, esea ch-based insigh s and p inciples o guiding ha p ac ice. In his si ua ion o de elopmen , a model based on TAM (Technology Accep ance Model) and low (essen ially de ined as an in insically enjoyable expe ience), is p oposed o desc ibe he main mo i es ha (1) a ec Web accep ance and usage and (2) make using he Web a compelling cus ome -expe ience. The pu pose o his s udy is hus o e eal whe he he e exis s he ela ion be ween low and TAM-belie s on he Web, and how he low impac s he a i ude and in en ion o use Web unde a heo e ically-based model. On he one hand, no e e yone has ag eed ha ex insic mo i es (e.g. how use ul he echnology would be) a e su icien . O e he yea s, he e is a g owing signi ican body o heo e ical and empi ical esea ch ega ding he impo ance o he ole o in insic mo i es (e.g. how enjoyable he echnology would be) in unde s anding ace s o beha iou (e.g., Bagozzi e al., 1999; Eas lick and Feinbe g, 1999; Hol , 1995; Hopkinson and Puja i, 1999; She man and Ma hu , 1997). Speci ically, he e is a signi ican body o heo e ical and empi ical e idence ega ding he impo ance o he ole o in insic mo i es in IT (In o ma ion Technologies) accep ance and use (see Da is e al., 1992; Malone, 1981; Venka esh and Speie , 1999, 2000; Webs e and Ma occhio, 1992). The e is hus he need o inco po a ing in insic mo i es and, in u n, ocusing on di e en beha iou - ypes (i.e. goal-di ec ed and expe ien ial). In ac , TAM-based s udies a e essen ially wo k ela ed and ocused on u ili a ian use (i.e. goal-di ec ed use). E en hough se e al pape s (e.g. Aga wal and Ka ahanna, 2000; Da is e al., 1992; Igba ia e al., 1996) ha e in oduced pe cei ed enjoymen in Web -as in insic mo i a ion-, hey s ill ocus on a ask-o ien ed pe spec i e. 4 The e o e, assuming by p e ious esea ch ha pe cei ed enjoymen could occu du ing goal- di ec ed ac i i ies, he e may be di e ences be ween goal-di ec ed and expe ien ial use s in he ela i e in luence o he se e al de e minan s o Web usage. Ac i i ies can be pe cei ed o be ins umen al –i.e. ex insic- in achie ing ou comes ha a e dis inc om he ac i i y i sel . Likewise, ac i i ies can be pe o med o no appa en ein o cemen o he han he p ocess o pe o ming he ac i i y –i.e. in insic-. Expe ien ial and goal-di ec ed use s would no hus weigh ex insic and in insic mo i es in he same way when on he Web. Fo ins ance, as Ho man e al. (2003) sugges , “ he gene al and b oad na u e o low measu emen o da e has p ecluded a p ecise in es iga ion o low du ing goal-di ec ed e sus expe ien ial ac i i ies”. Fu he mo e, “one impo an u u e esea ch a ea is speci ying and es ing concep ual amewo ks which di e en ia e expe ien ial and ask-o ien ed low. Concep ual models o low which ha e been de eloped and es ed o da e do no in any way di e en ia e be ween expe ien ial and ask-o ien ed low. The ela i e impo ance o an eceden s o low (…) may well di e ac oss a ional s expe ien ial p ocessing modes”. Ou objec i e is hus o e alua e he media ing ole o main ex insic and in insic mo i es explaining goal-di ec ed (i.e. o wo k and o sea ch o speci ic in o ma ion) and expe ien ial (i.e. adi ionally associa ed wi h ec ea ional su ing) accep ance and Web usage. The esul s could be used (1) o explain, and (2) o imp o e he use s’ expe ience o being and e u ning o he Web. This pape is ou lined as ollows. Fi s , he o iginal e sion o he TAM is in oduced. The nex sec ion s a s wi h a b ie ou line o he amewo k and p o ides 10 hypo heses ha can be de i ed om his amewo k. We hen desc ibe he esea ch me hod which was adop ed o alida e he model. Resul s and analysis ollow esea ch design. Finally, we gi e an in e p e a ion o he indings and discuss he con ibu ions and limi a ions o ou wo k. THEORETICAL BACKGROUND: A BRIEF PERSPECTIVE Resea ch in he HCI (Human-Compu e In e ac ion) adi ion has long asse ed ha he esea ch o human ac o s is a key o he success ul design and implemen a ion o echnological de ices, and should include ex insic and in insic mo i es. In his con ex and ollowing HCI-Resea ch in he 5 MIS (Managemen In o ma ion Sys em), indi iduals ha e a ull ange o oppo uni ies o in e ac wi h echnologies o di e en mo i es: ex insic o in insic. Mo i es ha e been cha ac e ized as in insic, emphasizing in e nal ewa ds such as pleasu e and sa is ac ion om pe o ming he beha iou , o ex insic, ocusing on ex e nal ewa ds including, o ins ance, incen i es and g a i ica ions. I is hus impo an o conside di e en he mo i es based, espec i ely, on he TAM and he low expe ience o unde s and he accep ance and Web usage. Technology Accep ance Model (TAM) Se e al esea ches ha e demons a ed he alidi y o TAM ac oss a wide a ie y o IT, also including E-Mail and Web. Speci ically and ocusing ou s udy on Web accep ance and usage, TAM sugges s ha he e exis s a di ec and posi i e e ec be ween a i ude owa ds Web usage, usage in en ion and ac ual usage. Pe cei ed use ulness and ease o use de e mine he a i udes owa d using he Web. In u n, usage in en ions a e de e mined by hese a i udes and pe cei ed use ulness. Finally, usage in en ions lead o ac ual Web use. :: Take in Figu e 1 :: Pe cei ed use ulness is de ined as “ he deg ee o which a pe son belie es ha using a pa icula sys em would enhance his o he job pe o mance” (Da is, 1989); as we commen ed abo e, he pe cep ion ha use s will wan o pe o m an ac i i y “because i is pe cei ed o be ins umen al in achie ing alued ou comes ha a e dis inc om he ac i i y i sel , such as imp o ed job pe o mance, pay, o p omo ions” (Da is e al., 1992). Pe cei ed ease o use is de ined as “ he deg ee o which a pe son belie es ha using a pa icula sys em would be ee o e o ” (Da is 1989). On he one hand, pe cei ed use ulness in luences Web usage indi ec ly h ough a i ude and di ec ly h ough in en . On he o he hand, as pe cei ed ease o use has an in e se ela ionship wi h he pe cei ed complexi y o use o he echnology, i a ec s pe cei ed use ulness. TAM hus posi s ha pe cei ed use ulness is in luenced by pe cei ed ease o use. A sys em ha is di icul o use is less likely o be pe cei ed as use ul; in o he wo ds, be ween wo sys ems o e ing iden ical unc ionali y, a use should ind he one ha is easie o use mo e use ul. Ne e heless, pe cei ed use ulness is no hypo hesized o ha e an impac on pe cei ed ease o use. Da is 6 (1993) s a es ha "(…) making a sys em easie o use, all else held cons an , should make he sys em mo e use ul. The con e se does no hold, howe e ”. Da is (1989) s a ed his o iginal TAM model whe e he ound a s onge suppo o pe cei ed ease o use cons uc wi h pe cei ed use ulness a he han wi h in en ion o use. “F om a causal pe spec i e, he eg ession esul s sugges ha ease o use may be an an eceden o use ulness, a he han a pa allel, di ec de e minan o usage”. La e , Da is (1993) no ed ha pe cei ed ease o use may ac ually be a p ime causal an eceden o pe cei ed use ulness. These ela ionships ha e been examined and suppo ed by many p io s udies (e.g., Da is, 1989, 1993; Da is e al., 1989; Venka esh and Da is, 1996, 2000). Howe e , as we commen ed abo e, he e is a signi ican body o heo e ical and empi ical e idence ega ding he impo ance o he ole o in insic mo i es in Web accep ance and use. Resea che s ha e become inc easingly awa e o he ele ance o he non-ex insic mo i es o use such as in insically-enjoyable expe iences (i.e., low) in unde s anding a i udes and beha iou s. Following, we e alua e he ole o low (1) a ec ing he Web-based beha iou as a highly-subjec i e a iable among indi iduals, and, in u n, (2) explaining and imp o ing he use s’ expe ience o being in and e u ning o he Web. Flow Model Flow, de ined as “ he holis ic sensa ion ha people eel when hey ac wi h o al in ol emen ” (Csikszen mihalyi, 1975), has been ecommended as a possible me ic o he online use expe ience (Kou a is, 2002). Flow is a posi i e, highly-enjoyable s a e o consciousness ha occu s when ou pe cei ed skills ma ch he pe cei ed challenges we a e unde aking. When his occu s an indi idual de i es in insic enjoymen om he ac i i y and ends o con inue wi h i . This is known as a s a e o low. I he ask is oo easy he pe son becomes bo ed. I he wo k demands skills beyond he capabili ies o he indi idual, anxie y is c ea ed. When ou goals a e clea , ou abili ies a e up o he challenge and eedback is immedia e. We become in ol ed in he ac i i y and in insically mo i a ed. 7 A common measu e o low could be hus he le el o pe cei ed enjoymen o an ac i i y, simila o he emo ional esponse o pleasu e om en i onmen al psychology (see Kou a is, 2002). In ac , as Da is e al. (1989) s a ed, pe cei ed enjoymen can be concep ualized as “ he ex en o which he ac i i y o using he compu e is pe cei ed o be enjoyable in i s own igh , apa om any pe o mance consequences ha may be an icipa ed”. Flow emphasizes a use 's subjec i e enjoymen o he in e ac ion wi h he echnology, no a pe cep ion o he medium pe se (T e ino and Webs e , 1992). Tha is o say, he concep o low is a possible me ic o he online use expe ience, and could be de ined as an in insically enjoyable expe ience. Many ex ensions o he o iginal TAM ha e been p oposed. Wi hin he IS domain, Da is e al. (1992) applied mo i a ional heo y o unde s and new echnology adop ion and use. These au ho s p oposed a new model, mo i a ional model (MM). One ac o was enamed (use ulness  ex insic mo i a ion) and one addi ional ac o was in oduced (pe cei ed enjoymen as in insic mo i a ion). As we no ed abo e, ex insic mo i a ion desc ibes an indi idual’s pe sonal gain associa ed wi h he use o a pa icula echnology. On he con a y, in insic mo i a ion desc ibes he pe cei ed enjoymen associa ed o he use o a pa icula echnology i sel , di e en om possible pe o mance ou come o he use (see also Valle and, 1997, o a ecen e iew). MM and TAM ha e concep ual and empi ical simila i ies; in ac , use ulness and ex insic mo i a ion a e qui e simila . Venka esh e al. (2002) in oduced an ex ending TAM, which in eg a es he in insic mo i a ion ac o om he mo i a ional model wi h he o iginal TAM. The measu es o in insic mo i a ion included enjoymen wi h he sys em, pleasance o sys ems use, and un o sys ems use. Mos ecen ly, Kou a is (2002) applied low heo y o online consume beha iou o examine emo ional and cogni i e esponses when isi ing an online s o e. This au ho expec ed engagemen wi h he si e would esul in in en ion o e u n o he s o e, ou lined ea lie as e- loyal y. Resul s p o ed ha p oduc in ol emen , web skills, alue-added sea ch mechanisms, and challenges ( o pe o m o bes o use ’s abili y and ‘s e ching’ use capabili ies) led o shopping enjoymen , and ul ima ely o in en ion o e u n o he si e. In his sense, in insically pe cei ed enjoymen has been iden i ied as an impo an in insic- mo i a ional ac o in Web accep ance and usage. Fo example, Da is e al. (1992) heo ised ha 8 pe cei ed enjoymen di ec ly in luenced compu e -usage in en ion (i.e. a wo d p ocessing p og am, W i eOne). Also, Igba ia e al. (1996) s udied he e ec o pe cei ed un-enjoymen . In his s udy, suppo was ound o a posi i e ela ionship be ween pe cei ed un-enjoymen and sys em usage among manage s and p o essionals who ei he had a mic ocompu e on hei desk o had ease access o one in he daily pe o mance o hei job. Pe cei ed enjoymen associa ed by an indi idual wi h a pa icula ac , could hus ha e a majo impac on an indi idual’s a ec i e esponse o he Web, i s a i udes and beha iou s. Howe e , al hough ega ding p e ious esea ch pe cei ed enjoymen could occu du ing goal-di ec ed ac i i ies, expe ien ial use s a e speci ically mo ed by an in insic mo i e (e.g. " o eel pleasu e and enjoymen om he ac i i y i sel "; Bloch e al., 1986), whe eas among goal-di ec ed use s b owsing appea s o in ol e mo e ex insic ewa ds han in insic ewa ds. The e migh be hus di e ences be ween goal-di ec ed and expe ien ial use s in he ela i e in luence o he a ious de e minan s (e.g. low s a e) o Web accep ance and usage. Expe ien ial use s show i ualized o ien a ions explo ing he Web in hei daily ques o he la es in e es ing si es. Use s sea ch o hose oppo uni ies which p o oke hem o u he explo e Web si es. Thus, expe ien ial use s do no essen ially alue he Web as a medium ha le s hem achie e se goals, bu hey b owse o ien a ed owa ds enjoyable na iga ional choices. I is an au o elic expe ience, whe e he expe ience i sel ac s as a p ima y in insic ewa d, e en i ex ensi e ex e nal ewa ds a e p esen . On he con a y, when usage is ex insic, ins umen al issues such as pe cei ed use ulness ough o come in o one's main decision making c i e ia o u u e usage (adap ed om Chin e al., 1996). Using he Web o i s in o ma ional alue and pu chase u ili y -such as di ec ly sea ching o in o ma ion o comple e a ask o o educe pu chase unce ain y- a e goal-di ec ed beha iou s, whe eas ela i ely uns uc u ed ec ea ional use a e expe ien ial beha iou s (see Ho man and No ak, 1996). As Ho man and No ak (1996) summa ized, “goal-di ec ed low ac i i ies in a CME a e ins umen al and u ili a ian in na u e, ex insically mo i a ed, cha ac e ized by si ua ional in ol emen , and esul in di ec ed sea ch and lea ning. In con as , expe ien ial low ac i i ies a e 9 i ualis ic and hedonic, in insically mo i a ed, cha ac e ized by endu ing in ol emen , and esul in non di ec ed sea ch and lea ning”. See Table 1. :: Take in Table I :: The e o e, expe ien ial and goal-di ec ed use s would no weigh ex insic and in insic mo i es in he same way when on he Web. Expe ien ial use s a e in ol ed in he ac i i y o he a ec i e esponses i p o ides (desi e o enjoymen plus explo a ion and play ulness) a he han o u ili a ian pu poses. We could hus ind ele an di e ence in (1) he ela ion be ween low and TAM-belie s on he Web, and how (2) he low impac s he a i ude and in en ion o use Web. Speci ically, in insic mo i es -such as pe cei ed enjoymen - should in luence on a i ude owa ds usage and in en ion g ea e among expe ien ial use s han among goal-di ec ed use s. This posi i e subjec i e expe ience becomes an impo an eason o accep ance and pe o mance an ac i i y among expe ien ial use s e en hough hey conside e he Web as ela i ely low in pe cei ed use ulness. On he con a y, goal-di ec ed use s may be willing o ole a e (i.e. accep and use) an annoying in e ace in o de o access o unc ionali y (as a salien and expec ed ewa d) - ha is he mos impo an -, while low will no be able o compensa e o a sys em ha doesn’ do a use ul ask. Likewise, acco ding o sel -pe cep ion heo y (see Bem, 1972) and he o e -jus i ica ion e ec (see Leppe e al. 1973), when people a ibu e hei beha iou o ex e nal ewa ds, hey discoun in e es as a cause o hei beha iou , and in insic mo i a ion will be, he e o e, lowe . I o malizes he idea emphasized in he psychology li e a u e ha he subjec inds he ask less a ac i e when o e s an expec ed and salien ewa d o engaging in an o he wise enjoyable ask. Tha is o say, he subjec would hen in e ha beha iou is mo i a ed by he ewa d i sel a he han by in insically pe cei ed-enjoymen . This e ec will be s onge when ex e nal ewa d is a ocus o cen al a en ion (i.e. goal-di ec ed use s) because he non-dis ac ion inc eases he endency o subjec s o hink abou he ewa d. On he con a y, expe ien ial use s usually engage in uns uc u ed ec ea ional ha educes hei endency o hink abou a possible ex e nal ewa d. Based on he abo e commen s, we p opose he ollowing hypo hesis. See Figu e 2. 16 hem. As Csikszen mihalyi (1997) summa izes, “when a pe son is anxious o wo ied, o example, he s ep o low o en seems oo a , and one e ea s o a less challenging si ua ion ins ead o ying a cope”. O he wise, oo much s imula ion will lead expe ien ial use s o making e o s and eel ou o con ol (i.e., anxie y as a nega i e a ec i e eac ion owa d Web use). The mo e confiden and com o able use eels on he Web, he mo e likely i is ha he/she will enjoy i . The e o e, based on he abo e e idence, we p opose he ollowing hypo hesis. See Figu e 2. H9. Highe le els o pe cei ed ease o use will be posi i ely ela ed o highe le els o low (i.e., pe cei ed enjoymen ) H9.a: The ela ionship be ween ease o use and low (i.e., pe cei ed enjoymen ) will be simila be ween expe ien ial use s and goal-di ec ed use s Because TAM is used as he baseline model, we also e i y he ollowing TAM hypo hesized ela ionship in he con ex o Web. H10. In en ion o use posi i ely in luences Web usage highe le els o in en ion o use will be posi i ely ela ed o highe le els o Web usage :: Take in Figu e 2 :: METHOD A su ey ins umen was used o ga he da a o es he ela ionships shown in he esea ch model. Da a we e collec ed om a sample o online ques ionnai es illed ou by subsc ibe s loca ed in h ee discussion-mailing lis s –adminis e ed by RedI is- abou di e en opics (e.g. expe imen al sciences, social sciences and humani ies) in o de o inc ease he di e si y o esponden s. On he one hand, ou a ge use s should decla e using Web equen ly o expe ien ial ( anged om 5-7 on EXP1-i em, and anged om 1-3 on GOAL1-i em see below) o goal-di ec ed ( anged om 5-7 on GOAL1-i em, and anged 1-3 on EXP1-i em) ac i i ies, adap ing he desc ip ions p oposed by Ho man e al. (2003). The i ems we e measu ed using a se en-poin scale anging 17 om “s ongly disag ee” o “s ongly ag ee”. Responden s a e hus clea as o he ac i i y con ex wi hin which hey a e esponding. GOAL1. Goal-di ec ed beha iou . I usually ha e a dis inc o iden i iable pu pose o my b owsing. EXPE1. Expe ien ial beha iou . I usually su o ha e no p econcei ed pu pose o my Web expe ience. The exclusion o in alid ques ionnai es due o duplica e submissions o ex ensi e emp y da a ields esul ed in wo inal samples: (1) expe ien ial use s (221 indi iduals); plus (2) goal-di ec ed use s (119 indi iduals). Thei main demog aphic-cha ac e is ics -age and sex- a e simila o an a e age In e ne use (6 h AIMC In e ne Use Su ey, Oc obe -Decembe , 2003). Sample demog aphics o he subjec s a e shown in Table II. :: Take in Table II :: On he o he hand, in de eloping he su ey ins umen , we chose bo h single i em and mul iple i em cons uc s. Single i em ques ions had o be selec ed o some cons uc s (a i ude and usage) because he su ey was deemed o be oo leng hy when e e y cons uc had mul iple i ems. Fo he i em cons uc s we adap ed measu es used in he e iewed li e a u e (see Da is, 1989; Da is e al., 1989; Ghani and Deshpande, 1994; No ak e al. 2000; Olney e al., 1991; Raman and Leckenby, 1998; Van de Heijden, 2001). Speci ically, acco ding o pe cei ed use ulness and ease o use scales, we adap ed Da is ‘s (1989) scales. One addi ional i em was in oduced and adap ed (“B owsing is in e es ing”, adap ed om Van de Heijden, 2001) and one o iginal i em (“B owsing in my job would enable me o accomplish asks mo e quickly“; adap ed om Da is, 1989) was omi ed because a p e ious analysis conside ed i included in o he i ems ela ed o p oduc i i y and e iciency. Adams e al. (1992) eplica ed he wo k o Da is (1989) o demons a e he alidi y and eliabili y o his ins umen and his measu emen scales. They also ex ended i o di e en se ings and, using wo 18 di e en samples, hey demons a ed he in e nal consis ency and eplica ion eliabili y o he wo scales. On he o he hand, Web use s' low expe iences a e mul i-dimensional (Chen e al., 1999). Flow is a complica ed cons uc . In ou s udy, we ha e es ima ed low by measu ing enjoymen and concen a ion (see Ghani and Deshpande, 1994; Olney e al., 1991). The domain o con en co e ed by he measu es (i.e. enjoymen and concen a ion) is clea ly speci ied and he measu es cons i u e a ele an census o he con en domain. As we commen ed abo e, pe cei ed enjoymen is ela ed o he psychological concep o “ low” (Csikszen mihalyi, 1975), which is desc ibed as an “in insically enjoyable expe ience”. In his sense, we ope a ionalize in insic enjoymen as b owsing enjoymen . Olney e al.’s (1991) ou -i em indices o hedonism we e used o measu e he enjoymen expe ienced while b owsing. Also, acco ding o Csikszen mihalyi and Csikszen mihalyi (1988), when one is in low, “one simply does no ha e enough a en ion le o hink abou any hing else”. Use in ol emen is a key d i e o use esponse and highe le els o in ol emen s imula e use s o be mo e a en i e o he in o ma ion p esen ed o hem (see And ews and Shimp, 1990; Pe y e al., 1983). We measu e i wi h a ou -i em scale adap ed om Ghani and Deshpande (1994). Howe e , wo i ems (“I am deeply eng ossed in ac i i y”-“I am abso bed in ensely in ac i i y”) co ela ed highly (>0.90, p < 0.000) in bo h samples -once ansla ed in o Spanish-; he o me was elimina ed o a oid a edundancy. Flow was hus measu ed as a second-o de cons uc , encompassing wo i s -o de cons uc s: (1) enjoymen ; and (2) concen a ion. The i ems o he dimension ‘ low’ we e op imally weigh ed and combined using he PLS algo i hm (PLS Ve sion 3.00 Build 1058, Chin, 2003) o c ea e la en a iable sco es. The esul ing sco e mo e accu a ely o m o p ecede he unde lying cons uc han any o he indi idual i ems by accoun ing o he unique ac o s and e o measu emen s ha may also a ec each i em (adap ed om Chin and Gopal, 1995). As a esul , he dimensions o i s - o de ac o s become he obse ed indica o s o second-o de ac o . Howe e , he p esence o 19 mul icollinea i y was also checked and he low a ia ion in la ion ac o (VIF < 10) indica ed ha mul icollinea i y o he esea ch da a was no o a conce n. As Williams e al. (2003) no e, “mul idimensional cons uc s a e o en concep ualized as composi es o hei dimensions, such ha he pa hs un om he dimensions o he cons uc . In such ins ances, he dimensions o he cons uc a e analogous o o ma i e indica o s, (…) as opposed o he e lec i e indica o s. Second, he indica o s o a mul idimensional cons uc a e no mani es a iables (…), bu ins ead a e speci ic la en a iables ha signi y he dimensions o he cons uc . These la en a iables equi e hei own mani es a iables as indica o s, such ha he mani es a iables and he mul idimensional cons uc a e sepa a ed by la en a iables ha cons i u e he dimensions o he cons uc ”. In ou esea ch, we ha e hus decided o p opose a mola second-o de ac o . Flow is (1) iewed as a composi e o enjoymen and concen a ion and (2) modelled as o ma i e 1 . In his sense, “indica o s could be iewed as causing a he han being caused by he la en a iable measu ed by he indica o s” (see MacCallum and B owne, 1993). In ac , he omission o a o ma i e indica o may al e he cons uc i sel . Fo ma i e indica o s can hus ouch upon di e en aspec s o he composi e a iable. Acco ding o he Web-usage a iable, i was ope a ionalised by a sel - epo ed measu e o ‘ he a e age ime ha an indi idual spends on a Web session’ adap ed by a a iable employed by Raman and Leckenby (1998) o measu e Web in e ac ion and No ak e al. (2000) o measu e imeuse. As Ga dne and Amo oso (2004) summa ize, “ hough some esea ch sugges s ha sel - epo ed usage measu es a e biased (S aub e al., 1995), o he esea ch sugges s ha sel - epo ed usage measu es co ela e well wi h ac ual usage measu es (see Taylo and Todd, 1995a; Venka esh and Da is, 2000)”. Howe e , as he Web beha iou o ou in e es is neu al and no pa icula ly sensi i e (as da a abou income, e hnici y, inancial p ac ices, e c), sel - epo s end o be accu a e (adap ed om Ajzen, 1988). 1 Howe e , we es ed wo e sions o he model -(1) wi h all cons uc s e lec i e and (2) wi h low cons uc o ma i e- and he esul s we e quali a i ely he same: no pa hs gained o los s a is ical signi icance, and no signi ican pa hs changed in sign. Thus, he eade may be con iden ha he esul s a e no an a i ac o he au ho ' modelling decisions. 20 The ques ionnai e is included in his pape ’s Appendix I. We p oposed inally 22 i ems co esponding o 7 cons uc s -plus a demog aphic sec ion-. Ou s udy was p og ammed o lis he ques ions in a andom o de o each pa icipan , a oiding po en ial sys ema ic biases in he da a. The scales we e measu ed using a se en-poin scale anging om “s ongly disag ee” o “s ongly ag ee” o uni y scale ypes, excep ing he usage cons uc in which indica o was measu ed anging om “ e y li le” o “ e y much”. Da a Analysis A S uc u al Equa ion Modeling (SEM), speci ically Pa ial Leas Squa e (PLS), is p oposed o assess he ela ionships be ween he cons uc s oge he wi h he p edic i e powe o he esea ch model. PLS was in en ed by He man Wold, as an analy ical al e na i e o si ua ions whe e heo y is weak and whe e he a ailable mani es a iables o measu es would be likely no o con o m o a igo ously-speci ied measu emen model. In ecen yea s, PLS p ocedu e has been gaining in e es and use among IS esea che s (Aube e al., 1994; Chin and Gopal, 1995; Compeau and Higgins, 1995; Roldán and Leal, 2003). We ha e used he Pa ial Leas Squa es (PLS) echnique because his ool is p ima ily in ended o p edic i e analysis in which he explo ed p oblems a e complex, and heo e ical knowledge is sca ce. As s a ed by Wold (1985), "PLS comes o he o e in la ge models, when he impo ance shi s om indi idual a iables and pa ame e s o packages o a iables and agg ega e pa ame e s. (…) In la ge, complex models wi h la en a iables PLS is i ually wi hou compe i ion". Fu he mo e, low-cons uc is measu ed wi h o ma i e indica o s. PLS is app op ia e o analyses o measu emen models wi h bo h o ma i e and e lec i e i ems. Being an eme gen cons uc , hey canno be easily modelled using LISREL and o he co a iance-based app oached since hese app oaches implici ly assume all indica o s o be e lec i e (Diaman opoulos and Winklho e , 2001). 21 Acco dingly, Pa ial Leas Squa es ia PLS-G aph 3.00 Build 1058 (Chin 2003) was used o analyse he da a. The s abili y o he es ima es was es ed ia a boo s ap e-sampling p ocedu e (500 sub-samples). PLS model is analyzed and in e p e ed in wo s ages: (1) he assessmen o he eliabili y and alidi y o he measu emen model, and (2) he assessmen o he s uc u al model. This sequence ensu es ha he cons uc s’ measu es a e alid and eliable be o e a emp ing o d aw conclusions ega ding ela ionships among cons uc s (Ba clay e al. 1995). RESULTS Measu emen model Fo hose cons uc s wi h e lec i e measu es (i.e. la en cons uc s), one examines he loadings, which can be in e p e ed in he same manne as he loadings in a P incipal Componen Analysis. Fo cons uc s using o ma i e measu es (i.e. eme gen cons uc s), he weigh s p o ide in o ma ion as o wha he makeup and ela i e impo ance a e o each indica o in he c ea ion/ o ma ion o he componen . They a e simila o when in e p e ing a canonical co ela ion analysis (Sambamu hy and Chin, 1994). Besides, i is necessa y o bea in mind ha no in e dependencies among he o ma i e i ems can be assumed, since he cons uc is iewed as an e ec a he han a cause o he i em esponses. The e o e, indica o s a e no necessa ily co ela ed and, consequen ly, adi ional eliabili y and alidi y assessmen ha e been a gued as inapp op ia e and illogical o his ype o high o de ac o (mola ) wi h e e ence o i s dimensions (Bollen, 1989). Thus, in ou s udy, examina ions o co ela ions o in e nal consis ency a e i ele an o eme gen cons uc s ( low-cons uc ). Indi idual e lec i e i em eliabili y is conside ed adequa e when an i em has a ac o loading ha is g ea e han 0.707 on i s espec i e cons uc , which implies mo e sha ed a iance be ween he cons uc and i s measu es (indica o s) han e o a iance (Ca mines and Zelle , 1979). All he e lec i e indi idual i em loadings in ou inal models a e abo e 0.707, excep ing EASE6 (0.6891, 22 expe ien ial-use s model; 0.6680, goal-di ec ed-use s’ model). The esul s ob ained a e hus accep able conside ing he explo a o y na u e o ou s udy. See Tables III and IV below. Cons uc eliabili y analyses he in e nal consis ency o a gi en block o indica o s. This is assessed using he composi e eliabili y (ρc) (We s e al., 1974). We can use he guidelines o e ed by Nunnally (1978) who sugges s 0.7 as a benchma k o a modes eliabili y applicable in ini ial s ages o esea ch. In ou esea ch, all o he la en cons uc s a e eliable. They all ha e measu es o in e nal consis ency ha exceed 0.7 (ρc). Also, we ha e checked he signi icance o he loadings wi h a e-sampling p ocedu e (500 sub-samples) o ob aining -s a is ic alues. They all a e signi ican . See Tables III and IV below. :: Take in Tables III and IV :: A e age a iance ex ac ed (AVE) (Fo nell and La cke , 1981) assesses he amoun o a iance ha a cons uc cap u es om i s indica o s ela i e o he amoun due o measu emen e o . I is ecommended ha AVE should be g ea e han 0.50 meaning ha 50% o mo e a iance o he indica o s should be accoun ed o . All la en a iables o ou models exceed his condi ion. See Tables III and IV abo e. Disc iminan alidi y indica es he ex en o which a gi en cons uc is di e en om o he la en a iables. To assess disc iminan alidi y, AVE should be g ea e han he a iance sha ed be ween he la en cons uc and o he la en cons uc s in he model (i.e. he squa ed co ela ion be ween wo cons uc s) (Ba clay e al., 1995). All la en a iables sa is y his condi ion. Fo his eason, we main ain he disc iminan alidi y o he la en cons uc s o he models. See Tables V and VI below. :: Take in Tables V and VI :: S uc u al model 23 Tables VII o IX show he hypo heses, pa h coe icien s (), - alues, and he a iance explained (R2) in he dependen cons uc s. Figu e 2 shows a g aphical ep esen a ion o he pa h coe icien s () and he R2 alues ( a iance accoun ed o ) in he dependen a iables, which allows a be e unde s anding o he s uc u al model. Consis en wi h Chin (1998), boo s apping (500 esamples) was used o gene a e s anda d e o s and -s a is ics. Suppo o each gene al hypo hesis on bo h samples can be de e mined by examining he sign and s a is ical signi icance o he - alues o i s co esponding pa h. See Table VII and Figu e 2. :: Take in Table VII :: :: Take in Figu e 3 :: Bo h esea ch models seem o ha e an app op ia e p edic i e powe o mos o he dependen a iables. The mean o he explained a iance o he implied a iables is 44.5% and 42.6% o expe ien ial and goal-di ec ed use g oups espec i ely. See Table VIII. :: Take in Table VIII :: Mo eo e , hypo heses on in ensi y di e ences be ween bo h ypes o use s (Hia) could be es ed by s a is ically compa ing co esponding pa h coe icien s in hese s uc u al models. This s a is ical compa ison was ca ied ou using he p ocedu e sugges ed by Chin (2000) o de elop a mul i- g oup analysis, which was implemen ed in Keil e al. (2000). Acco ding o his p ocedu e, a - es is calcula ed ollowing he Equa ion 1, which ollows a -dis ibu ion wi h m+n-2 deg ees o eedom, whe e Sp (Equa ion 2) is he pooled es ima o o he a iance, m and n a e he sample o expe ien ial and goal-di ec ed use s g oup espec i ely, and SE is he s anda d e o o pa h in he s uc u al model. Resul s a e desc ibed in Table IX, p esen ing a wide suppo o he hypo heses pu o wa d. :: Take in Equa ion 1 and 2: :: Take in Table VII :: Finally, since he s udy is a c oss-sec ional su ey, i is p oblema ic o d aw causal in e ences, and hus we a oid asse ing causali y in ou commen s. Also, acco ding o he app oach ollowed by 24 he Pa ial Leas Squa es echnique, i.e. so modeling, he concep o causa ion mus be eplaced by he concep o p edic abili y (Falk and Mille , 1992). As can be seen om Tables VII and IX, he da a suppo ed he model and all hypo heses canno be ejec ed on he basis o his empi ical da a. In en ion. Acco ding o H10, in en ion is expec ed o ha e a posi i e ela ionship o usage; he ela ionship was ound in bo h samples (expe ien ial and goal-di ec ed use s). A i ude. H5 hypo hesises a posi i e ela ionship be ween a i ude and in en ion o use Web in bo h samples. The pa hs suppo he ela ionships hypo hesised. This implies ha a i ude owa ds usage is a ele an media o be ween pe cep ions and in en ion o use. Also, he ela ionship was signi ican ly g ea e among expe ien ial use s han among goal-di ec ed use s, suppo ing H1a. Use ulness. In gene al, use ulness was expec ed o ha e a posi i e ela ionship o: a i ude owa ds usage, H4, and in en ion o use, H3. On he one hand, he ela ionship use ulness –> a i ude was ound in bo h samples and, on he o he hand, i was lesse among expe ien ial use s han among goal-di ec ed use s, hus suppo ing H4a. The ela ionship H3 (use ulness  in en ion o use Web), was no signi ican among expe ien ial use s, he eby pa ly ejec ing H3. A possible explana ion o his can be summed up in he ollowing way: expe ien ial use s would no engage in an expe ien ial and play ul beha iou ha also inc eases ex insic ewa ds wi hou p e iously adjus ing hei a i udes. The e o e, use ulness in luences on in en ion o use Web among goal- di ec ed use s a e g ea e han among expe ien ial use s, suppo ing H3a. Ease o Use. The e we e posi i e disce nible ela ionships be ween ease o use  a i ude (H6), ease o use  low (H9) and ease o use  use ulness (H7), hus suppo ing he ci ed hypo heses in bo h samples. Speci ically, he pa h coe icien s (ease o use  a i ude, H6; ease o use  use ulness, H7) we e signi ican and s a is ically di e en be ween expe ien ial use s and goal- di ec ed use s; also, he ela ionships suppo he p oposed in ensi ies (H6a and H7a). The in ensi y o he ela ionship H9 (ease o use  low) was simila be ween expe ien ial use s and among goal-di ec ed use s, suppo ing H9a 25 Flow. H1 hypo hesises a posi i e ela ionship be ween low and a i ude owa ds usage in bo h samples. The pa h-coe icien suppo s he sign. Fu he , he hypo hesised in ensi y (H1a) was ound among goal-di ec ed and expe ien ial use s. H2 hypo hesises a posi i e ela ionship be ween low and in en ion o use Web; he pa h-coe icien s suppo he ela ionship hypo hesised. H8 posi s a posi i e ela ionship be ween low and use ulness. The ela ionship was no signi ican among goal-di ec ed use s, he eby ejec ing H8. Goal-di ec ed use s would be willing o ole a e an annoyed in e ace in o de o access unc ionali y ha is e y impo an , while no amoun o low will be able o inc ease pe cei ed use ulness o a sys em ha doesn’ do a use ul ask. Also, H2a and H8a posi g ea e in luences among expe ien ial use s han among goal-di ec ed use s. Bo h ela ionships we e signi ican ly g ea e among expe ien ial use s han among goal-di ec ed use s, suppo ing H2a and H8a. R2. A numbe o indings - ela ed o low- a e wo h men ioning in pa icula (see Tables X and XI). The ela i e impac o low on he beha iou al in en ion can be examined by compa ing he change in i s R2 alue when low is emo ed om he model (see Table X). The e ec size 2 can be calcula ed as ((R2 ull – R2excluded)÷(1 – R2 ull)). Cohen (1988) sugges ed 0.02, 0.15, and 0.35 as ope a ional de ini ions o small, medium and la ge e ec sizes espec i ely (see Chin, 1998). Excluding low om he i s model (based on expe ien ial use s) esul ed in a d op o R2 o 0.398; in con as , excluding low om he second model (based on goal-di ec ed use s) esul ed in a d op o R2 o 0.382. The ela i e impac o low on he beha iou al in en ion was hus simila be ween expe ien ial use s ( 2 = 0.0524) and goal-di ec ed use s ( 2 = 0.0474). Fu he mo e, acco ding o ela i e impac o low on he a i ude owa ds usage (see Table XI), excluding low om he i s model (based on expe ien ial use s) esul ed in a d op o R2 o 0.524 ( 2 = 0.1018). 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(2001), “Human-Compu e In e ac ion Resea ch in he MIS Discipline,” Communica ions o he Associa ion o In o ma ion Sys ems, Vol. 9, pp. 334-355. 38 Figu e 1. Technology Accep ance Model Use ulness Ease o use A i ude UsageIn en ion 39 Table I. Dis inc ions be ween goal-di ec ed and expe ien ial beha iou Goal-di ec ed Expe ien ial Ex insic mo i a ion In insic mo i a ion Ins umen al o ien a ion Ri ualized o ien a ion Si ua ional in ol emen Endu ing in ol emen U ili a ian bene i s/ alue Hedonic bene i s/ alue Di ec ed (p epu chase) sea ch Nondi ec ed (ongoing) sea ch; b owsing Goal-di ec ed choice Na iga ional choice Cogni i e A ec i e Wo k Fun Planned pu chases; epu chasing Compulsi e shopping; Impulse buys Sou ce: Ho man e al. (2003) 40 Table II. Desc ip i e s a is ics o esponden s' cha ac e is ics Use s Ou s udy* 6 h AIMC In e ne Use Su ey Expe ien ial Goal-di ec ed Age < 20 10.0 12.4 10.9 20-24 27.5 25.5 23.1 25-34 32.2 30.8 38.7 35-44 19.6 15.6 17.2 45-54 10.0 12.3 7.4 55-64 0.7 3.0 2.2 >64 0.0 0.4 0.4 N/A 0.0 0.0 0.2 Sex Males 68.0 65.1 71.6 Females 32.0 34.9 28.1 % es ima ed o e samples o expe ien ial and goal-di ec ed use s 41 Figu e 1. Hypo heses Use ulness Ease o use A i ude UsageIn en ion Flow H4 and H4a H10 H5 and H5a H8 and H8a H7 and H7a H6 and H6a H9 and H9a H2 and H2a H3 and H3a H1 and H1a 48 Table VIII. Va iance explained (R2) o expe ien ial and goal-di ec ed s uc u al models Indica o s Expe ien ial use s Goal-di ec ed use s In en ion 0.428 0.410 A i ude 0.568 0.575 Use ulness 0.359 0.471 Flow 0.301 0.287 Ease o Use -.- -.- Web Usage 0.573 0.389 49 Equa ion 1. T-s a is ic wi h m+n–2 deg ees o eedom nm Sp di ec edGoalalExpe ien i 11     50 Equa ion 2. Pooled es ima o o he a iance 22 )2( )1( )2( )1( di ec edGoalalExpe ien i SE nm n SE nm m Sp         51 Table IX. T- es s o mul i-g oup analysis H0 S anda d e o s (SE) Sp E - GD T- alue Suppo ed H0 Expe ien ial Goal- di ec ed F  A H1a E>GD 0.0825 0.0716 0.0789 0.1150 12.824*** Suppo ed F  I H2a E>GD 0.0757 0.0743 0.0752 0.0420 4.911*** Suppo ed U  I H3a GD>E 0.0710 0.0816 0.0749 -0.1190 -13.979*** Suppo ed U  A H4a GD>E 0.0806 0.0867 0.0828 -0.2620 -27.836*** Suppo ed A  I H5a E>GD 0.0325 0.1135 0.0720 0.0710 8.672*** Suppo ed EOU  A H6a E>GD 0.1058 0.0624 0.0930 0.1950 18.445*** Suppo ed EOU  U H7a GD>E 0.0811 0.0798 0.0806 -0.3170 -34.569*** Suppo ed F  U H8a E>GD 0.0792 0.0953 0.0852 0.2470 25.507*** Suppo ed EOU  F H9a E=GD 0.0581 0.0816 0.0672 0.0130 1.700ns Suppo ed *** p < 0.001, ** p < 0.01, * p < 0.05, ns = no signi ican (based on (338), wo- ailed es ) (0.001; 338) = 3.319543035; (0.01; 338) = 2.590452926; (0.05; 338) = 1.967007242 52 Table X. Impac o independen a iables on in en ion o use Independen a iables Samples R2 ull R2 excluded 2 F A i ude Expe ien ial 0.428 0.340 0.1538** Signi ican Goal-di ec ed 0.410 0.353 0.0966* Signi ican Use ulness Expe ien ial 0.428 0.421 0.0122 ns No signi ican Goal-di ec ed 0.410 0.391 0.0322* No signi ican Flow Expe ien ial 0.428 0.398 0.0524* Signi ican Goal-di ec ed 0.410 0.382 0.0475* Signi ican *Small: 0.02; **medium: 0.15; ***la ge e ec : 0.35; ns: no signi ican 53 Table XI. Impac o independen a iables on a i ude owa ds use Independen a iables Samples R2 ull R2 excluded 2 F Ease o Use Expe ien ial 0.568 0.495 0.1690** Signi ican Goal-di ec ed 0.575 0.566 0.0212* No signi ican Use ulness Expe ien ial 0.568 0.512 0.1296* Signi ican Goal-di ec ed 0.575 0.407 0.3953*** Signi ican Flow Expe ien ial 0.568 0.524 0.1019* Signi ican Goal-di ec ed 0.575 0.555 0.0471* Signi ican *Small: 0.02; **medium: 0.15; ***la ge e ec : 0.35; ns: no signi ican 54 Appendix I. Scales* CONSTRUCT/Indica o s INTENTION**  INTEN1 Gi en ha I ha e access o he Web, I in end o use i  INTEN2 Gi en ha I ha e access o he Web, I p edic ha I would use i ATTITUDE**  ATTIT1 I ha e a posi i e a i ude owa ds using he Web USEFULNESS  UTILI1 B owsing imp o es my pe o mance  UTILI2 B owsing inc eases my p oduc i i y  UTILI3 B owsing enhances my e ec i eness  UTILI4 B owsing is in e es ing  UTILI5 B owsing is use ul ENJOYMENT  ENJOY1 B owsing Web is pleasan  ENJOY2 B owsing Web is un  ENJOY3 B owsing Web is en e aining  ENJOY4 B owsing Web is enjoyable CONCENTRATION  CONCEN1 When I b owse, I am abso bed in ensely in b owsing  CONCEN2 When I b owse, I concen a e ully on b owsing  CONCEN3 When I b owse, my a en ion is ocused on b owsing EASE OF USE  EASE1 Lea ning o b owse is easy o me  EASE2 I ind i easy o ge Web o do wha I wan i o do  EASE3 My in e ac ion wi h Web is clea and unde s andable  EASE4 I ind Web o be lexible o in e ac wi h  EASE5 I is easy o me o become skill ul a using Web  EASE6 I ind easy o b owse USAGE  USAGE1 On a e age, how much ime would you es ima e ha you pe sonally spend on each Web session? * Ful illed in Spanish and hen ansla ed in o English ** In ou p oposal ‘B owsing’ is employed as using-synonymous.